千万级数据索引优化策略与实践

java复制代码
// 假设使用MySQL数据库，JDBC连接数据库  
String url = "jdbc:mysql://localhost:3306/your_database";  
String user = "your_username";  
String password = "your_password";  
String createIndexSql = "CREATE INDEX idx_your_column ON your_table(your_column)";  
try (Connection conn = DriverManager.getConnection(url, user, password);  
Statement stmt = conn.createStatement()) {  
    stmt.executeUpdate(createIndexSql);  
    System.out.println("Index created successfully.");  
} catch (SQLException e) {  
    e.printStackTrace();  
}

java复制代码
// 创建聚集索引（通常作为主键）  
String createClusteredIndexSql = "CREATE TABLE your_table (" +  
"id INT PRIMARY KEY, " + // 聚集索引  
"name VARCHAR(255), " +  
"age INT, " +  
// ... 其他列  
")";  
// 创建覆盖索引  
String createCoveringIndexSql = "CREATE INDEX idx_name_age ON your_table(name, age)"; // 覆盖查询"SELECT name, age FROM your_table WHERE name = ?"  
// 执行SQL语句...（省略，与上面类似）

java复制代码
// 监控索引使用情况的示例（简化版）  
String queryPlanSql = "EXPLAIN SELECT * FROM your_table WHERE your_column = ?";  
try (Connection conn = DriverManager.getConnection(url, user, password);  
PreparedStatement pstmt = conn.prepareStatement(queryPlanSql)) {  
    pstmt.setString(1, "your_value");  
try (ResultSet rs = pstmt.executeQuery()) {  
while (rs.next()) {  
// 分析查询计划结果  
            System.out.println(rs.getString("Explain Plan")); // 注意：实际列名可能是"id"、"select_type"等，根据数据库而定  
        }  
    }  
} catch (SQLException e) {  
    e.printStackTrace();  
}